Thematic Maps

What Is a Thematic Map?

Most published and online maps fall into four categories:

  • Navigation maps, including topographic maps and nautical and aeronautical charts

  • Geophysical maps, that show the structure and dynamics of earth, oceans and atmosphere

  • Location maps, that depict the locations and names of physical features

  • Thematic maps, that portray attribute data about locations and features

Although online maps often combine these categories in new and unexpected ways, published maps and atlases tend to respect them.

Thematic maps tend to be more highly stylized than other types of maps and frequently omit locational information such as place names, physical features, coordinate grids, and map scales. This is because rather than showing physical features on the ground, such as shorelines, roads, settlements, topography, and vegetation, a thematic map displays quantified facts (a "theme"), such as statistics for a region or sets of regions. Examples include the locations of traffic accidents in a city, or election results by state. Thematic maps have a wide vocabulary of cartographic symbols, such as point symbols, dot distributions, "quiver" vectors, isolines, colored zones, raised prisms, and continuous 3-D surfaces. Mapping Toolbox™ functions can generate most of these types of map symbology.

Choropleth Maps

The most familiar form of thematic map is probably the choropleth map (from the Greek choros, for place, and plethos, for magnitude). Choropleth maps use colors or patterns to represent attributes associated with certain geographic regions. For example, the global distribution of malaria-carrying mosquitoes can be illustrated in a choropleth map, with the habitat of each mosquito represented by a different color. In this example, colors are used to represent nominal data; the categories of mosquitoes have no inherent ranking. If the data is ordinal, rather than nominal, the map may contain a colorbar with shades of colors representing the ranking. For instance, a map of crime rates in different areas could show high crime areas in red, lower crime areas in pink, and lowest crime areas in white.

Creating choropleth maps with the Mapping Toolbox is fairly straightforward. Start with a geographic data structure; create a symbolspec to map attribute values to face colors; and apply either geoshow or mapshow, depending on whether you are working with latitude-longitude or pre-projected map coordinates. The following example illustrates the process of creating a choropleth map of population density for the six New England states in the year 2000.

  1. Set the map limits for the New England region. Import low-resolution U.S. state boundary polygons:

    MapLatLimit = [41 48];
    MapLonLimit = [-74 -66];
    
    NEstates = shaperead('usastatelo', 'UseGeoCoords', true, ...
       'BoundingBox', [MapLonLimit' MapLatLimit']);
  2. Set up map axes with a projection suitable to display the New England states:

    axesm('MapProjection', 'eqaconic', 'MapParallels', [],...
      'MapLatLimit', MapLatLimit, 'MapLonLimit', MapLonLimit,...
      'GLineStyle', '-')
    
  3. Display the New England states:

    geoshow(NEstates, 'DisplayType', 'polygon', 'FaceColor','green')
    

  4. Identify the maximum population density for New England states:

    maxdensity = max([NEstates.PopDens2000]);
    
  5. Create an autumn colormap for the six New England states, and then use the flipud command to invert the matrix.

    fall = flipud(autumn(numel(NEstates)));
    
  6. Make a symbol specification structure, a symbolspec, that assigns an autumn color to each polygon according to the population density.

    densityColors = makesymbolspec('Polygon', {'PopDens2000', ...
       [0 maxdensity], 'FaceColor', fall});
    
  7. Display the map.

    geoshow(NEstates, 'DisplayType', 'polygon', ...
       'SymbolSpec', densityColors)
    title ({'Population Density in New England in 2000', ...
       'in Persons per Square Mile'})
  8. Create a colorbar.

    caxis([0 maxdensity])
    colormap(fall)
    colorbar

  9. Experiment with other colormaps. Some names of predefined colormaps are autumn, cool, copper, gray, pink, and jet.

Special Thematic Mapping Functions

In addition to choropleth maps, other Mapping Toolbox display and symbology functions include

Function

Used For

cometm

Traces (animates) vectors slowly from a comet head

comet3m

Traces (animates) vectors in 3-D slowly from a comet head

quiverm

Plots directed vectors in 2-D from specified latitudes and longitudes with lengths also specified as latitudes and longitudes

quiver3m

Plots directed vectors in 3-D from specified latitudes, longitudes, and altitudes with lengths also specified as latitudes and longitudes and altitudes

scatterm

Draws fixed or proportional symbol maps for each point in a vector with specified marker symbol. Similar maps can be generated using geoshow and mapshow using appropriate symbol specifications ("symbolspecs").

stem3m

Projects a 3-D stem plot map on the current map axes

The cometm and quiverm functions operate like their MATLAB® counterparts comet and quiver. The stem3m function allows you to display geographic bar graphs. Like the MATLAB scatter function, the scatterm function allows you to display a thematic map with proportionally sized symbols. The tissot function calculates and displays Tissot Indicatrices, which graphically portray the shape distortions of any map projection. For more information on these capabilities, consult the descriptions of these functions in the reference pages.

Stem Maps

Stem plots are 3-D geographic bar graphs portraying numeric attributes at point locations, usually on vector base maps. Below is an example of a stem plot over a map of the continental United States. The bars could represent anything from selected city populations to the number of units of a product purchased at each location:

Contour Maps

Contour and quiver plots can be useful in analyzing matrix data. In the following example, contour elevation lines have been drawn over a topographical map. The region displayed is the Gulf of Mexico, obtained from the topo matrix. Quiver plots have been added to visualize the gradient of the topographical matrix.

Here is the displayed map:

Scatter Maps

The scatterm function plots symbols at specified point locations, like the MATLAB scatter function. If the symbols are small and inconspicuous and do not vary in size, the result is a dot-distribution map. If the symbols vary in size and/or shape according to a vector of attribute values, the result is a proportional symbol map.

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